AI systems developed in response to COVID-19: Survey

During the pandemic, health ecosystems have changed dramatically. WPF has been engrossed in researching these changes, and is participating in multiple stakeholder groups assessing the impact of the pandemic on privacy interests. One of our activities is in the OECD AI Observatory, where we are a delegate in the ONE AI working group on implementing trustworthy AI.

Currently, the AI Observatory has an open survey that is of interest to stakeholders who have developed one or more AI systems in direct response to the COVID-19 pandemic. This survey will assist the OECD in creating an interoperable classification of these systems and observing best practices as well as use cases. The survey is open until August 2, 2021 and will take 15-25 minutes to complete.

The data collected from this survey will be shared in an open access GPAI labeled repository. The data will be part of a “living repository” to facilitate knowledge sharing of the systems using AI in the pandemic response.

The survey is available at the OECD Observatory: https://oecd.ai/wonk/pandemic

Posted July 29, 2021 in AI, COVID-19, Digital Health Ecosystems

New Report: Risky Analysis: Assessing and Improving AI Governance Tools

We are pleased to announce the publication of a new WPF report, “Risky Analysis: Assessing and Improving AI Governance Tools.” This report sets out a definition of AI governance tools, documents why and how these tools are critically important for trustworthy AI, and where these tools are around the world. The report also documents problems in some AI governance tools themselves, and suggests pathways to improve AI governance tools and create an evaluative environment to measure their effectiveness. AI systems should not be deployed without simultaneously evaluating the potential adverse impacts of such systems and mitigating their risks, and most of the world agrees about the need to take precautions against the threats posed. The specific tools and techniques that exist to evaluate and measure AI systems for their inclusiveness, fairness, explainability, privacy, safety and other trustworthiness issues — called in the report collectively AI governance tools – can improve such issues. While some AI governance tools provide reassurance to the public and to regulators, the tools too often lack meaningful oversight and quality assessments. Incomplete or ineffective AI governance tools can create a false sense of confidence, cause unintended problems, and generally undermine the promise of AI systems. The report contains rich background details, use cases, potential solutions to the problems discussed in the report, and a global index of AI Governance Tools.
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Report: From the Filing Cabinet to the Cloud: Updating the Privacy Act of 1974

This comprehensive report and proposed bill text is focused on the Privacy Act of 1974, an important and early Federal privacy law that applies to the government sector and some contractors. The Privacy Act was written for the 1970s information era -- an era that was characterized by the use of mainframe computers and filing cabinets. Today's digital information era looks much different than the '70s: smart phones are smarter than the old mainframes, and documents are now routinely digitized and stored and perhaps even analyzed in the cloud, among many other changes. The report focuses on why the Privacy Act needs an update that will bring it into this century, and how that could look and work. This work was written by Robert Gellman, and informed by a two-year multi-stakeholder process.